Operations | Monitoring | ITSM | DevOps | Cloud

What is SharePoint document lifecycle? A guide to the stages a SharePoint document moves through, the Microsoft Purview tools that manage each stage, and where Squirrel handles the archive tier.

Everyone wants an AI agent factory in 2026. Autonomous agents fixing bugs and shipping features while you sleep. I’ve been building toward that myself. But the error rates don’t support the fantasy. The best AI coding agents in the world fix about 50% of real bugs on SWE-bench verified. Half the time they fail. And AI-generated code produces 1.7x more issues than human-written code.

For network administrators, managing DNS has traditionally meant juggling zones and records across separate server interfaces, manually tracking changes, and responding to resolution failures after they’ve already caused disruption. We’re excited to introduce Microsoft DNS management in ManageEngine OpUtils, bringing DNS zone and record administration directly into the same console you already use for IP address management (IPAM).

Software moves from code to production more quickly today, but it is still difficult to tell whether delivery is actually improving or just becoming more active. Most teams rely on dashboards filled with metrics like deployments, uptime, failures, and tickets. The numbers are available, but the meaning behind them is often unclear. DevOps metrics become useful only when grouped into clear categories: DORA metrics cover only delivery speed and stability, which is just part of the picture.

Some support cases are straightforward. Others lead deep into legacy code, where a single logic bug can quietly turn a routine command into a major performance problem. This series looks at how Canonical Support and Sustaining Engineering work together to investigate, patch, and upstream difficult issues that standard troubleshooting alone cannot solve.

Every application starts the same way: One server. One database. One optimistic engineer saying: “We’ll scale later.” And honestly? That’s usually the right call. Premature scaling is how perfectly normal applications end up with: But eventually, growth happens. Traffic increases. Queries slow down. Deployments get riskier. Your infrastructure starts making unfamiliar noises. This is where scaling enters the picture. Not scaling for conference talks.

CloudZero continues to ship new features and enhancements at a fast pace. We’re publishing these product update posts to keep you up to date on our velocity and how we’re adding customer value.

AI spend is going parabolic, and the labels on the bill (OpenAI, Anthropic, Gemini) are about all a CXO gets to work with. The hard part of tying that spend to outcomes is structural. A major portion of AI spend isn’t COGS. It’s the spend on coding agents producing the software, the spend on building marketing content, the spend on custom sales tooling, the spend on Intercom agents and Sybill analysis.